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Quality
Quality:Quality in its most simple terms may be defined as “Conformance to requirements”. A product is said to be of good quality if it works well in the equipment it was meant for. Quality is a relative term and is generally used with reference to the end use of the product. For example, a gear used in sugarcane juice machine may not possess good surface finish, tolerance & accuracy as compared to the gear used in say a lathe machine, still it may be considered of good quality if it works satisfactorily in the juice extracting machine. There are 3 stages in consideration of ‘Total Quality’ of any product (DCP) Quality of Design: It is concerned with the tightness of the specifications for the product. (For e.g. a part having a drawing tolerance of 0.001 mm would be considered to be of better quality than a part having a tolerance of 0.01 mm.) Quality of Conformance: It is concerned with how well the manufactured product conforms to the quality of design. Quality of Performance: It is concerned with how well the manufactured product gives its performance. It depends on q of Design and q of Conformance Quality control: “Control” may be defined as the process in which we observe the actual performance, compare it with some standard and if there if there is any deviation, necessary corrective actions are taken. Inspection & Quality Control Inspection just measures the quality of a product or service w.r.t predefined standards and does not involve any sort of corrective actions. It simply separates defective items from non-defective items. Quality Control on the other hand incorporates a feedback mechanism which involves identifying the cause of poor quality and taking corrective actions accordingly. Quality Assurance & Quality Control Quality Assurance is for the Process (i.e. the process for developing the product or service follow all the required quality standards) Quality Control is for the Product (i.e. the final product meets all the required quality standards) Quality assurance is the process of evaluating the factors which affect the quality of any product or service to give confidence that it will continue to maintain its quality level. Statistical quality control: A QC technique that applies the laws of probability and statistical techniques to the observed characteristics of a product or process. Control Chart for Variables X chart — for averages of samples R chart — for ranges of samples Control Chart for Attributes P chart — for Fraction Defectives C chart — for Defects Per Unit Lack of control is indicated by points falling outside control limits What is Process Capability? Process Capability is the total spread of the process. We expect the output to be spread over a band 12 σ units wide. (in 6σ –: spread =12 σ) Tolerance = Xmax – Xmin If T > PC => All the products will meet specifications as long as the process stay in control If T < PC => Defective parts will always be there ISO 9000/1400 ISO 9000 series of quality standards were formulated by International Organisation for Standardization in order to meet the requirements of an internationally uniform quality system. It includes …. ISO 9000 – gives guidelines for “selection & use” of appropriate model under this series. Quality assurance model for…… * ISO 9001 – Design development * ISO 9002 - Production & installation * ISO 9003 – Final inspection & testing * ISO 9004 – gives guidelines for “Quality Management” for maintaining quality culture in the organization So we see there are total “5” ISO 9000 standards….. 0 & 4 are guidelines; 0 for selecting appropriate model; 4 for maintaining a quality culture in the organisation. 1 gives quality assurance at all stages starting from designing the product & continuing even after the product is delivered to the customer (i.e. after sales services also) 2 gives quality assurance only during production i.e. it proves that the production system is capable of producing the product with required quality stanadards 3 gives quality assurance only to the final product i.e. the customer is not concerned with how they are manufactured Examples: # Heat exchangers, coolers, filters # Construction of bridges & other civil structures # Domestic appliances, components used in the assembly of bigger items such as automobiles (corresponding Indian standards are IS 14000, 1,2,3,4 ) ISO certifies that whatever is followed is being documented. ISO-14000 – the ISO-14000 series is an effort to level the field in terms of barriers to trade and competition and to ensure that organizations have a consistent environmental program in place. Probability Distributions Poisson - for situations which can be described by a discrete random variable that takes a whole no. value (0,1,2,3….) eg. No. of patients arriving at a health clinic in a given time interval , no. of vehicles arriving at a toll booth. The probability of exactly r occurrences in a Poisson distribution is given by – λr . e-λ P® = ---------- (λ = mean of distribution ) ∟r Normal – it’s a continuous probability distribution having a symmetric bell-shape It is applicable to a no. phenomenon eg. height of humans, (implies that most of the observations in a set of data are close to the average while relatively few are at one extreme or other.) Defined by 2 measures # Mean – which locates the center # Standard Deviation – which measures the spread around the center (range = - ∞ to + ∞) √ ∑ (x - x¯)2 σ = -------------- n σ = square root of the average of the squares of deviations from the mean of a set of data σ signifies how tightly all the values are clustered around the mean in a set of data Value of σ => describes uniformity Smaller the value, more is the uniformity 1 σ limits occupy 68 % of the area of the normal curve and indicates that we can say with 68% confidence that a random observation will fall in this area 2 σ = 95 % 3 σ = 99.73 % 6 σ = 99.9997 % For eg. consider that you are running a pizza delivery business and you set a target of delivering pizza’s within 25 minutes of receiving the order. Now if you achieve that 68 % of the time, you are running at 1 σ, if you achieve it 99.9997 % of the time then you are at 6 σ (means you are late on an average only 3.4 times out of every one million orders). This is fundamentally how 6 Sigma measures quality. It measures the Variance and does not rely on Mean What does 6 σ actually mean ? 6 σ is actually the Control Limits which gives a confidence level of 99.9997 % ie there thee is only 0.0034 % chances that a random observation will not represent the fact (ie it will fall outside the limits) The objective of six sigma is to reduce the process output variations. Binomial – Sampling inspection A random sample drawn from the lot represents the lot. Operating Characteristic curve (or OC curve) Percent defective Vs Probability of acceptance Producer’s risk: Probability of a good lot being rejected which otherwise should have been accepted. Purchaser’s risk: Probability of a bad lot being accepted which otherwise should have been rejected. Acceptable Quality Level: It is the maximum proportion of defective components up to which the lot is definitely acceptable Lot Tolerance Percent Defective: It is the minimum proportion of defective components which will make the lot definitely reject able Sampling by Attributes: Yes or No criteria; Where there is no need to measure exact dimensions and a go: no-go gauge can serve the purpose. (also where it is difficult to measure for eg quality of paint etc) Sampling by Variables: Measure exact dimensions Variable – uses averages of measurements Attributes – uses percentage of defectives Control Chart for Variables: X R σ Control Chart for Attributes: p c np u X, R – Process Control P – Fraction defectives C – Defects per unit X – chart for the measure of central tendency (shows changes in process average) R – chart for the measure of spread (shows general variability) Shows – erratic or cyclic shifts Steady progress change eg tool wear Eg For studying tool wear – X, R For large and complex parts – C Zero Defect Zero Defect is a quality improvement program which seeks voluntary participation of all the people in the organization to undertake personal responsibility for quality of task in hand. It motivates the employee to - Do it right the first time ;Quality Circle: Quality circle is a small group of employees working at one place, who voluntarily come forward to discuss their work related problems once in a week ;Reliability: Reliability is the probability of an item to perform its intended function for a given period of time under given operating conditions. = Total operating time of items (in unit-hrs.) / No. of units failed rate Z = 1/MTBF ; Reliability R = exp(-Zt) Reliability in series: R = R1 . R2 . R3 Reliability in parallel: R = R1 + R2 + R3 Availability Availability is the probability of an item to perform its intended function at any given time under given operating conditions. MTBF A = --------------------- MTBF + MTTR = total repair time/no. of stoppages Availability is of 3 types – Inherent, Achieved and Operational I – under ideal conditions A – takes into account time for preventive maintenance (in MDT) O – takes into account time for pm and supply and administrative time also (in MDT) (for A & O) -> MTBM = Total operating time/ No. of stoppages -> MDT = Total down time / No. of stoppages (reliability is function of time ; availability is not) Taguchi methods- these are methods aimed at quality improvement in both product and process design. They are based on making designs robust by building in tolerances for manufacturing variables known to be avoidable. Quality in Software Engineering In software a mere ‘fitness of purpose’ definition for quality won’t suffice. Eg even if a software performs all the functions as specified in the SRS (Software Requirement Specification) document, if it does not have a good user interface or its code is unmaintainable, we cannot say it of good quality. Thus the quality of any software depends on many factors such as -: Usability Maintainability Portability Correctness Capability Maturity Model (CMM) CMM is a process improvement model for software development given by Software Engineering Institute. The basic idea of CMM is that every organisation has a certain capability or maturity level to produce software. (Depending on the organisation’s current maturity level, CMM tells what aspects of software development should be addressed next to achieve next level of maturity.) CMM has established 5 Maturity Levels -: * Initial * Repeatability * Defined * Managed * Optimizing Initial => Software process is ad hoc and chaotic (lack of planning) Repeatability => Capability to repeat earlier success on projects with similar applications Defined => All projects follow a standard and well documented process Managed => Detailed quantitative measures for quality and productivity are collected Optimizing => Capable of continuous process improvement (through innovative ideas and new technologies) People Capability Maturity Model (P-CMM) Focuses on Human Assets of an organization It provides a model for improvement in the development and management of workforce. Aims at continuous improvement in the knowledge, skill and motivation of the people CMM is a model specifically designed for software development ISO 9000 is a generic model CMMI = CMM Integration Extending the idea to areas other than software development Home About_IE IE_1 Quality WorkStudy New_Tech Manufacturing Contribute Contact